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BERT_top5_bm25_rr5_10_epoch

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0294
  • Accuracy: 0.7708
  • F1: 0.6486
  • Precision: 0.5385
  • Recall: 0.8155

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 0.2623 16 0.6133 0.8237 0.5270 0.8667 0.3786
No log 0.5246 32 0.5112 0.7758 0.2393 1.0 0.1359
No log 0.7869 48 0.4725 0.8363 0.6448 0.7375 0.5728
No log 1.0492 64 0.3894 0.8539 0.6882 0.7711 0.6214
No log 1.3115 80 0.7018 0.5013 0.5 0.3379 0.9612
No log 1.5738 96 0.4207 0.8338 0.7054 0.6529 0.7670
No log 1.8361 112 0.4159 0.7834 0.6587 0.5570 0.8058
No log 2.0984 128 0.4052 0.8060 0.6831 0.5929 0.8058
No log 2.3607 144 0.4456 0.7859 0.6743 0.5570 0.8544
No log 2.6230 160 0.3880 0.8564 0.7016 0.7614 0.6505
No log 2.8852 176 0.5137 0.8262 0.5660 0.8036 0.4369
No log 3.1475 192 0.4837 0.7935 0.6496 0.5802 0.7379
No log 3.4098 208 0.7301 0.7280 0.6197 0.4862 0.8544
No log 3.6721 224 0.6014 0.8413 0.6866 0.7041 0.6699
No log 3.9344 240 0.7912 0.7456 0.6481 0.5054 0.9029
No log 4.1967 256 0.6779 0.7834 0.6587 0.5570 0.8058
No log 4.4590 272 0.6352 0.8010 0.6749 0.5857 0.7961
No log 4.7213 288 0.9313 0.7229 0.6207 0.4813 0.8738
No log 4.9836 304 0.7459 0.7758 0.6454 0.5473 0.7864
No log 5.2459 320 0.6967 0.8186 0.6636 0.6396 0.6893
No log 5.5082 336 0.7340 0.8086 0.6780 0.6015 0.7767
No log 5.7705 352 0.9585 0.7506 0.6374 0.5118 0.8447
No log 6.0328 368 0.8556 0.8010 0.6749 0.5857 0.7961
No log 6.2951 384 1.0044 0.7758 0.6590 0.5443 0.8350
No log 6.5574 400 1.0174 0.7809 0.6641 0.5513 0.8350
No log 6.8197 416 0.8044 0.8111 0.6888 0.6014 0.8058
No log 7.0820 432 1.0973 0.7204 0.6159 0.4785 0.8641
No log 7.3443 448 0.9667 0.7758 0.6537 0.5455 0.8155
No log 7.6066 464 0.7502 0.8438 0.7130 0.6814 0.7476
No log 7.8689 480 1.0102 0.7733 0.6617 0.5399 0.8544
No log 8.1311 496 0.9457 0.7783 0.6589 0.5484 0.8252
0.2259 8.3934 512 0.9533 0.7834 0.656 0.5578 0.7961
0.2259 8.6557 528 1.0134 0.7783 0.6589 0.5484 0.8252
0.2259 8.9180 544 1.0594 0.7632 0.6466 0.5276 0.8350
0.2259 9.1803 560 1.0415 0.7708 0.6566 0.5370 0.8447
0.2259 9.4426 576 1.0485 0.7683 0.6515 0.5342 0.8350
0.2259 9.7049 592 1.0386 0.7708 0.6540 0.5375 0.8350
0.2259 9.9672 608 1.0294 0.7708 0.6486 0.5385 0.8155

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Tokenizers 0.19.1
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